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基于互信息和归一化互信息的MRI和SPECT脑图像配准技术的准确性和可重复性。

Accuracy and reproducibility of co-registration techniques based on mutual information and normalized mutual information for MRI and SPECT brain images.

作者信息

Yokoi Takashi, Soma Tsutomu, Shinohara Hiroyuki, Matsuda Hiroshi

机构信息

Image Processing Division, Bioimaging Laboratory, Inc., Kyoto, Japan.

出版信息

Ann Nucl Med. 2004 Dec;18(8):659-67. doi: 10.1007/BF02985959.

Abstract

We implemented a 3D co-registration technique based on mutual information (MI) including 2D image matching as a coarse pre-registration. The 2D coarse pre-registration was performed in the transverse, sagittal and coronal planes sequentially, and all six parameters were then optimized as fine registration. Normalized mutual information (NMI) was also examined as another entropy-based measure that was invariant to the overlapped area of two images. In order to compare accuracy and precision of the present method with a conventional two-level multiresolution approach, simulation was performed by 100 trials with the random initial mismatch of +/-10 degrees and +/-17.92 mm (Type-I) and +/-20 degrees and +/-40.32 mm (Type-II). For Type-I, no significant differences were found between registration errors of the multiresolution approach and the present method with the MI criterion. No biases were observed (< or =0.13 degrees and < or =0.57 mm for the multiresolution approach; < or =0.12 degrees and < or =0.57 mm for the present method) and the SDs were very small (< or =0.18 degrees and < or =0.12 mm for the multiresolution approach; < or =0.11 degrees and < or =0.11 mm for the present method). For Type-II, SDs for the multiresolution approach (< or =1.8 degrees and < or =0.88 mm) were markedly larger than those for the present method (< or =0.64 degrees and < or =0.20 mm) with MI. Success rate for the present method was 99.9%, which was higher than 97.6% for the multiresolution approach. Simulation also revealed that MI and NMI performance were almost equivalent. The choice of optimization strategy more affected accuracy and reproducibility than the choice of the registration criterion (MI or NMI) in our simulation condition. The present method is sufficiently accurate and reproducible for MRI-SPECT registration in clinical use.

摘要

我们实施了一种基于互信息(MI)的三维配准技术,包括将二维图像匹配作为粗略的预配准。二维粗略预配准按顺序在横断面、矢状面和冠状面进行,然后对所有六个参数进行优化作为精细配准。归一化互信息(NMI)也作为另一种基于熵的度量进行了检验,它对两个图像的重叠区域具有不变性。为了将本方法的准确性和精确性与传统的两级多分辨率方法进行比较,进行了100次模拟试验,随机初始失配为+/-10度和+/-17.92毫米(I型)以及+/-20度和+/-40.32毫米(II型)。对于I型,多分辨率方法和采用MI准则的本方法的配准误差之间未发现显著差异。未观察到偏差(多分辨率方法<或=0.13度和<或=0.57毫米;本方法<或=0.12度和<或=0.57毫米),标准差非常小(多分辨率方法<或=0.18度和<或=0.12毫米;本方法<或=0.11度和<或=0.11毫米)。对于II型,采用MI时,多分辨率方法的标准差(<或=1.8度和<或=0.88毫米)明显大于本方法的标准差(<或=0.64度和<或=0.20毫米)。本方法的成功率为99.9%,高于多分辨率方法的97.6%。模拟还表明,MI和NMI性能几乎相当。在我们的模拟条件下,优化策略的选择比配准准则(MI或NMI)的选择对准确性和可重复性的影响更大。本方法在临床应用中用于MRI-SPECT配准具有足够的准确性和可重复性。

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